Dataset Versions
Versions
2024-10-13 10:04am
v26
· a month ago
2024-10-13 10:04am
v25
· a month ago
2024-10-13 10:03am
v24
· a month ago
2024-10-13 10:02am
v23
· a month ago
2024-10-13 10:01am
v22
· a month ago
2024-10-13 10:00am
v21
· a month ago
2024-10-13 9:59am
v20
· a month ago
2024-10-13 9:49am
v19
· a month ago
2024-10-13 9:35am
v18
· a month ago
2024-10-13 9:34am
v17
· a month ago
2024-10-13 9:32am
v16
· a month ago
2024-10-13 9:31am
v15
· a month ago
2024-10-13 9:30am
v14
· a month ago
2024-10-13 9:29am
v13
· a month ago
2024-10-13 9:28am
v12
· a month ago
2024-10-13 9:27am
v11
· a month ago
2024-10-13 9:26am
v10
· a month ago
2024-10-13 9:22am
v9
· a month ago
2024-10-13 9:13am
v8
· a month ago
2024-10-13 9:12am
v7
· a month ago
2024-10-13 9:10am
v6
· a month ago
2024-10-13 9:08am
v5
· a month ago
2024-10-13 9:03am
v4
· a month ago
2024-10-13 9:02am
v3
· a month ago
2024-10-13 9:01am
v2
· a month ago
2024-10-13 8:55am
v1
· a month ago
v19
2024-10-13 9:49am
Generated on Oct 13, 2024
Popular Download Formats
YOLOv11
TXT annotations and YAML config used with YOLOv11.
YOLOv9
TXT annotations and YAML config used with YOLOv9.
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
177 Total Images
View All ImagesDataset Split
Train Set 100%
177Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Fit within 25`x57
Augmentations
Outputs per training example: 3
Crop: 0% Minimum Zoom, 10% Maximum Zoom
Rotation: Between -2° and +2°